Little Computer People: A Survey and Taxonomy of Simulated Models of Social Interaction


Bolstered by a growing interest in simulating believable non-player characters (NPCs), work on NPC models has spanned topics such as planning, procedural storytelling, decision-making, and social dynamics. However, research groups work in isolation, designing and discussing their character models with disparate approaches, often using project-specific terminology. This makes it challenging to identify, classify, and accumulate existing knowledge. It is our position that since modelling of virtual characters has become an integral part of the scientific practice in our field, we must develop a common taxonomy to discuss these models. With this goal in mind, we conduct an in-depth analysis of a selection of projects, categorizing existing agent social interactions, and comparing results from research-based and commercial social simulation works in the entertainment domain. We conceptualize a taxonomy that classifies agent interactions by their social behaviours, inter-agent communication, knowledge flow, and the change in their relationships. We posit such a taxonomy would allow scientists to reproduce and evaluate existing models, collaborate on standards, share advances with other researchers and practitioners, allow for better communication and methodologies developed for new techniques, and allow for a more rigorous model-to-model analysis.

CHI Play 2021 - Proceedings of the ACM on Human-Computer Interaction
Sasha Azad
Ph.D. Computer Science Candidate

Sasha Azad is a Ph.D. Computer Science candidate at NC State University. Her main research interests lie in the field of Human-Centered Artificial Intelligence, AI for Storytelling, AI for Social Simulation, and Computational Social Science.